In order to provide more relevant search results to a user, queries and the uniform resource locators (URLs) that are subsequently clicked upon are classified into a classification index. The queries and URLs are assigned to a particular category, which is also referred to as a knowledge domain. The knowledge domain generally defines the subject matter that a user was seeking when the query was presented to the search engine.
Most common random feed (CRF) classifiers use machine-based learning, using both negative and positive queries to train the classifiers. This process uses iteration to fill in missing gaps, and can also take several months to develop. In addition, classifiers need to be changed or updated frequently, which makes the overall process resource expensive.